APIs or streamline routine processes. But if you’ve landed on this guide, chances are you’re evaluating whether StackAI might offer something more, particularly if your organization is navigating AI adoption, data governance, or large-scale automation needs.

This guide dives into the key differences between the two platforms, not just in features but also in philosophy, design, and enterprise readiness, so you can choose the right solution for your team.

TL;DR Comparison

To make your decision easier, we’ve put together a clear, side-by-side breakdown of StackAI and n8n. This comparison covers everything from AI features and workflow builders to security, enterprise support, and pricing.

Interface & User Experience

Workflow Builder (drag-and-drop vs node-based editor)

n8n uses a linear, node-based editor designed primarily for developers. Each step must be connected in a fixed sequence, and building even moderately complex flows often requires handling JSON, writing JavaScript, and configuring API calls manually. There’s no drag-and-drop canvas, no parallel logic, and no built-in support for LLMs in the UI.

StackAI, on the other hand, offers a visual drag-and-drop builder on a 2D canvas, inspired by tools like Miro. You can arrange and connect LLMs, data sources, logic nodes, and third-party apps freely, without writing code. The interface supports parallel logic, AI-based routing, and gives you a clear, bird’s-eye view of your workflows.

The result is not just greater speed, it’s greater flexibility. While n8n flows are typically linear and developer-owned, StackAI enables cross-functional collaboration and supports multi-agent orchestration directly within the interface.

Agent Builder (LLM orchestration, multi-step agents)

n8n does not include a native agent builder. Creating an AI assistant usually involves:

• Manual prompt chaining

• Custom context handling

• External RAG setup for document Q&A

• Managing LLM APIs and outputs individually

StackAI’s Agent Builder simplifies all of this. You can go from idea to working assistant in just a few minutes:

• Connect internal documents (Google Drive, Notion, SharePoint)

• Choose an LLM (OpenAI, Claude, Mistral)

• Click “Publish” with no code required

Every agent includes:

• Document-aware chat with grounding

• Citations and follow-up prompts

• Tool actions such as setting reminders or querying Salesforce

This is ideal when you need to launch something quickly without relying on an AI ops team.

Exportable Interfaces (APIs, chatbots, batch inputs, forms)

In StackAI, once your workflow or agent is ready, you can instantly publish it as:

• A chatbot embedded on a site

• A web form for teammates

• A batch processor for bulk uploads

• A secure link for sharing

• A REST API for backend use

n8n workflows are always available as API endpoints, which works well for backend automation. But if you need user-facing experiences like a chatbot or internal tool, you’ll need to build them yourself and connect them manually.

📽️ Want to see it in action?

Here’s a 3-minute walkthrough showing StackAI’s visual builder, Agent Builder, and deployable interfaces in action:

Core Capabilities & AI Features

AI Routing & Logic Nodes (if/else paths, dynamic flows)

StackAI includes built-in logic components that support if/else conditions, multi-branch decision trees, and dynamic prompting based on LLM outputs. This allows agents to adapt their behavior in real time depending on the context, input, or internal state of the workflow. It’s ideal for use cases that require AI-based decision-making.

n8n offers similar control through function and switch nodes, but it requires more manual setup and doesn’t support AI-native routing out of the box. Logic must be explicitly coded or scripted and cannot leverage LLM context without external configuration.

Knowledge Bases & Retrieval-Augmented Generation (RAG)

StackAI offers native RAG support through its Knowledge Base node, which automatically handles chunking, embedding, indexing, and retrieval. Users can upload files or connect cloud storage, and the content becomes immediately accessible for LLM-based Q&A with citations and metadata included.

n8n does not include native RAG functionality. Achieving similar results requires connecting third-party vector databases like Pinecone or Supabase and manually handling data preprocessing, embedding, and retrieval logic.

Data Handling (large documents, PDFs, scraping, structured files)

StackAI is designed to work with real-world, messy data. It includes built-in tools for PDF parsing, web scraping, large document processing, and transforming unstructured content into structured formats. All of this happens directly inside the platform, with no plugins or external tools required.

n8n can handle similar data types, but it typically relies on third-party integrations or custom scripts. Working with large files or extracting clean data from PDFs and websites often involves extra configuration and external services.

📽️ Want to see how it works in practice?

Here’s a short video showing how StackAI handles PDFs, web pages, and large documents inside a single workflow:

Batch Processing & Multi-input management

StackAI supports batch execution out of the box. You can process multiple files, rows, or requests through the same workflow. This is ideal for document pipelines, bulk data extraction, or multi-user scenarios. No extra scripting is required.

n8n can handle batch-like workflows, but it typically involves manual loop logic and does not provide native batching at the agent level.

Observability & Monitoring (logs, usage analytics, agent insights)

StackAI provides detailed observability across all projects. It includes usage metrics, token consumption, input and output logs, latency insights, and agent version history. For sensitive environments, logging can be disabled to maintain data privacy.

n8n offers basic execution logs and error tracking, which is useful for debugging. However, it lacks dedicated analytics for LLM usage, cost insights, or agent-level performance monitoring.

Integrations & Extensibility

App Integrations

StackAI comes with native integrations for both enterprise systems and modern SaaS tools. Out of the box, users can connect to platforms like Salesforce, SAP, Workday, SharePoint, Netsuite, and Snowflake, along with apps like Miro, Notion, Typeform, and Slack. These integrations are designed for AI-first workflows, enabling seamless ingestion of data from legacy systems and cloud environments alike.

Here’s a breakdown of key integration areas by department:

You can explore the full list of supported integration. In addition to built-in connectors, StackAI supports MCP (Modular Connector Protocol) making it possible to integrate with third-party-hosted tools not natively available in the platform.

n8n supports hundreds of SaaS integrations, and is especially strong with tools like Gmail, Slack, and PostgreSQL. However, it lacks built-in connectors for many enterprise platforms. Integrating with tools like SharePoint or SAP typically requires manual configuration, third-party middleware, or custom development.

LLM & AI Model Integrations

StackAI integrates natively with OpenAI, Anthropic (Claude), Mistral, Google, Meta, Azure OpenAI, and local LLMs via endpoint, giving users maximum flexibility to choose and switch providers. There’s no need to manage API keys manually. StackAI handles authentication, rate limits, and fallback logic internally.

n8n supports LLMs through custom HTTP requests or plugins, but model setup, error handling, and switching must be done manually. There’s no built-in UI for managing LLM settings or deploying multi-model strategies.

Developer Features (custom APIs, SDKs, Python nodes)

StackAI offers a flexible developer layer that makes it easy to extend workflows when custom logic is needed. Technical teams can:

• Use Python nodes for custom logic and advanced processing

• Call external systems through API nodes and webhooks

• Build internal tools with the StackAI SDK

• Add custom “tools” that can be triggered directly by LLMs (function calling)

📽️ Want to see how it works? This video walks through all the developer capabilities:

n8n is also highly extensible and developer-friendly, especially for classic automation workflows. However, it lacks native primitives for building AI-first agents, tools, or RAG pipelines, which limits its out-of-the-box support for modern LLM use cases.

Governance, Security & Compliance

Role-based Access Control

StackAI offers granular role-based access control (RBAC) at both the project and workspace levels. Teams can define exactly who can view, edit, publish, or interact with agents and workflows. Built-in approval workflows, publishing restrictions, and detailed access logs make it easy to maintain tight control over sensitive deployments. These controls are designed to support both regulated industries and large, multi-team environments where governance is critical.

n8n provides basic access control features in its cloud version, including roles like Admin, Editor, and Viewer. For teams using the self-hosted version, more advanced permissions can be configured, but they require manual setup and ongoing maintenance. While flexible, this setup depends heavily on your internal technical resources.

Privacy & Compliance

StackAI is fully compliant with SOC 2 Type II, HIPAA, and GDPR standards. It includes built-in features like PII detection and masking, data retention policies, and on-premise deployment options, making it suitable for industries where data governance and auditability are non-negotiable. Also, StackAI guarantees no data is used for training under enterprise contracts.

n8n does not hold formal compliance certifications. Self-hosting may give teams more control over data handling, but it also puts the burden of compliance entirely on the organization, including managing audits, encryption, and access policies.

Scalability & Performance (agent orchestration, concurrent flows)

StackAI is built for enterprise scale, supporting high-concurrency workloads, multi-agent orchestration, and simultaneous users working across departments. It provides infrastructure-level controls to manage performance, stability, and resource allocation.

n8n can scale through self-managed deployments, but supporting high concurrency or large teams requires custom infrastructure, external orchestration, and ongoing maintenance.

Deployment Options (Cloud, Private Cloud, On-prem)

StackAI supports flexible deployment models, including public cloud, private cloud, and fully on-premise installations. All deployment types include the same feature set, making it easier to switch or scale based on internal IT or regulatory requirements.

n8n offers a cloud-hosted version and the option to self-host. While powerful, the on-premise setup is more hands-on and often requires additional devops resources for enterprise-level scalability and compliance.

📽️ Want a quick look at StackAI’s governance features? This video covers user roles, data access controls and security settings.

Support

StackAI includes dedicated onboarding sessions, access to solution engineers, and priority support with defined SLAs. Enterprise customers also receive quarterly business reviews (QBRs) to align on goals, use cases, and roadmap planning.

n8n provides email support for enterprise customers, while most day-to-day help comes through the community, GitHub issues, and forum posts.

Who It’s For

Target Audience

StackAI is built for business-first, AI-first organizations. It’s ideal for:

• Business teams (Ops, Finance, Legal, Compliance, Customer Support) looking to build and deploy AI copilots or assistants without relying on engineering

• IT and transformation leaders who need a platform that meets strict governance, access control, and security standards

• Enterprise environments where collaboration between technical and non-technical teams is key, and where workflows often span legacy systems like SharePoint, SAP, and Workday

• Industries with high regulatory overhead, such as financial services, insurance, healthcare, and government — where on-premise deployment and full auditability are essential

n8n, by contrast, is tailored to technical users who prefer full control over every step of their automation:

• Developers, DevOps, and automation engineers building custom scripts and backend flows

• Teams already familiar with JSON, APIs, and JavaScript who want a flexible toolkit for connecting apps and transforming data

• Startups, tech teams, or agencies that want open-source software with full self-hosting flexibility

• Companies with well-defined, repetitive processes that can be fully automated through nodes and API integrations

Ideal Use Cases

StackAI excels in AI-powered scenarios where logic, data, and user interaction need to be orchestrated with context:

• Internal AI copilots for finance, HR, legal, IT support, or knowledge management

• Document-heavy workflows like parsing contracts, financial statements, claims, or internal policies

• AI research agents that combine document search (RAG), scraping, and API lookups to generate insights

• Compliance and audit workflows that require approval flows, version control, and PII masking

• Cross-departmental tools with exportable interfaces (chatbots, forms, batch upload tools) and usage analytics

• Scenarios where business teams need autonomy but IT requires visibility and governance

n8n is a strong fit for classic automation patterns driven by events or APIs:

• Webhook automations (e.g., trigger when a form is submitted or email is received)

• SaaS data syncing between tools like Google Sheets, Slack, Airtable, and CRM platforms

• Backend logic that involves simple conditionals, loops, and data transformations

• Custom API orchestration for internal tools or microservices

• Dev-led projects where flexibility, plugins, and code injection are more important than user interfaces or LLM integration

Final Take

• Choose StackAI if you want to roll out AI copilots quickly, stay compliant, and let business teams build without code while IT keeps full oversight.

• Choose n8n if you’re a tech-forward team that values open-source flexibility, prefers scripting things your way, and doesn’t mind managing your own setup.